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Designing efficient methods for the tandem AGV network design problem using tabu search and genetic algorithm

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Abstract

A tandem AGV configuration connects all cells of a manufacturing facility/plant by means of non-overlapping, single-vehicle closed loops. Each loop has at least one additional P/D station, provided as an interface between adjacent loops. This study describes the development of tabu search and genetic algorithm procedures for designing tandem AGV systems. The objective is to minimize the maximum workload of the system. Both algorithms have mechanisms to prevent solutions with intersecting loops. The new algorithms and the partitioning algorithm presented by Bozer and Srinivasan are compared using randomly generated test problems. Results show that for large-scale problems, the partitioning algorithm often leads to infeasible configurations with crossed loops in spite of its shorter running time. However the newly developed algorithm avoids infeasible configurations and often yields better objective function values.

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Authors and Affiliations

  1. Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran

    Reza Zanjirani Farahani, Elnaz Miandoabchi & Saman Bina

  2. Canada Research Chair in Distribution Management and GERAD, HEC Montréal, 3000 chemin de la Côte-Sainte-Catherine, Montreal, H3T 2A7, Canada

    Gilbert Laporte

  3. Supply Chain Management Research Group, Tehran, Iran

    Saman Bina

Authors
  1. Reza Zanjirani Farahani
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  2. Gilbert Laporte
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  3. Elnaz Miandoabchi
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  4. Saman Bina
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Corresponding author

Correspondence to Reza Zanjirani Farahani.

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Zanjirani Farahani, R., Laporte, G., Miandoabchi, E. et al. Designing efficient methods for the tandem AGV network design problem using tabu search and genetic algorithm. Int J Adv Manuf Technol 36, 996–1009 (2008). https://doi.org/10.1007/s00170-006-0909-4

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  • DOI: https://doi.org/10.1007/s00170-006-0909-4

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